aws_bedrock_embeddings

beta

Available in: Cloud, Self-Managed

Generates vector embeddings from text prompts, using the AWS Bedrock API.

  • Common

  • Advanced

# Common config fields, showing default values
label: ""
aws_bedrock_embeddings:
  model: amazon.titan-embed-text-v1 # No default (required)
  text: "" # No default (optional)
# All config fields, showing default values
label: ""
aws_bedrock_embeddings:
  region: ""
  endpoint: ""
  credentials:
    from_ec2_role: false
    role: ""
    role_external_id: ""
  model: amazon.titan-embed-text-v1 # No default (required)
  text: "" # No default (optional)

This processor sends text prompts to your chosen large language model (LLM), which generates vector embeddings for them using the AWS Bedrock API.

For more information, see the AWS Bedrock documentation.

Fields

credentials

Manually configure the AWS credentials to use (optional). For more information, see the Amazon Web Services guide.

Type: object

credentials.from_ec2_role

Use the credentials of a host EC2 machine configured to assume an IAM role associated with the instance.

Type: bool

credentials.id

The ID of the AWS credentials to use.

Type: string

credentials.profile

The profile from ~/.aws/credentials to use.

Type: string

credentials.role

The role ARN to assume.

Type: string

credentials.role_external_id

An external ID to use when assuming a role.

Type: string

credentials.secret

The secret for the AWS credentials in use.

This field contains sensitive information that usually shouldn’t be added to a configuration directly. For more information, see Manage Secrets before adding it to your configuration.

Type: string

credentials.token

The token for the AWS credentials in use. This is a required value for short-term credentials.

Type: string

endpoint

Specify a custom endpoint for the AWS API.

Type: string

model

The ID of the LLM that you want to use to generate vector embeddings. For a full list, see the AWS Bedrock documentation.

Type: string

# Examples:
model: amazon.titan-embed-text-v1
model: amazon.titan-embed-text-v2:0
model: cohere.embed-english-v3
model: cohere.embed-multilingual-v3

region

The region in which your AWS resources are hosted.

Type: string

text

The prompt you want to generate a vector embedding for. The processor submits the entire payload as a string.

Type: string